A study of academic performance of business school graduates using neural network and statistical techniques

被引：30

作者：

Paliwal, Mukta ^{[1
]}

Kumar, Usha A. ^{[1
]}

机构：

[1] Indian Inst Technol, Shailesh J Mehta Sch Management, Bombay 400076, Maharashtra, India

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2009年 / 36卷 / 04期

关键词：

Academic performance; Discriminant analysis; Logistic regression; Neural network; Regression analysis; REGRESSION;

D O I：

10.1016/j.eswa.2008.11.003

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Over the past several years, there is tremendous increase in the number of applicants to business schools and hence adequately measuring the potential of these Students with regard to their academic performance is an important process of admission decision for any business school. In the present study, an analysis is carried Out to predict the academic performance of business school graduates using neural networks and traditional statistical techniques and results are compared to evaluate the performance of these techniques. The underlying constructs in a traditional business school curriculum are also identified and its relevance with the various elements of admission process is presented. (C) 2008 Elsevier Ltd. All rights reserved.

引用

页码：7865 / 7872

页数：8

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